title: A method to estimate off-schedule observations in a longitudinal study.
abstract: OBJECTIVE
  Data in epidemiological studies sometimes are collected off-schedule from planned study visits. In an ancillary study to the Study of Women's Health Across the Nation (SWAN), longitudinal breast density data were collected retrospectively from mammograms that were not acquired at the study visits. We propose a method to estimate the off-schedule breast density measurements at the time of study visits.
  
  
  METHODS
  This method uses local linear interpolation, with multiply imputed error terms drawn from assumed subject-specific normal distributions based on the within-subject standard deviations of mammographic density measurements. We evaluate the validity and implications of this approach.
  
  
  RESULTS
  Coefficients of random intercept models used to assess the association between annual changes in body mass index and dense breast area estimated with this approach (β = -0.17, p = .46) differed from those obtained when each mammogram was matched to the nearest study visit (β = -0.30, p = .04). The proposed estimation approach had a small average prediction error (0.11 cm2).
  
  
  CONCLUSIONS
  Because matching does not incorporate breast density changes over time, our local linear interpolation with multiple imputation approach may provide more accurate results. The proposed approach is applicable to other epidemiologic studies with off-schedule data in which the missing variable changes linearly over relatively short periods of time.
authors.affiliation: Department of Public Health, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA. kwreeves@schoolph.umass.edu
authors.forename: Katherine W
authors.initials: KW
authors.lastname: Reeves
authors.forename: Roslyn A
authors.initials: RA
authors.lastname: Stone
authors.forename: Francesmary
authors.initials: F
authors.lastname: Modugno
authors.forename: Roberta B
authors.initials: RB
authors.lastname: Ness
authors.forename: Victor G
authors.initials: VG
authors.lastname: Vogel
authors.forename: Joel L
authors.initials: JL
authors.lastname: Weissfeld
authors.forename: Laurel A
authors.initials: LA
authors.lastname: Habel
authors.forename: Marike
authors.initials: M
authors.lastname: Vuga
authors.forename: Jane A
authors.initials: JA
authors.lastname: Cauley
mesh_terms: D015992:Body Mass Index; D003625:Data Collection / Q000379:methods* / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D003720:Densitometry / Q000379:methods / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies / Q000379:methods* / Q000706:statistics & numerical data*; D008327:Mammography / Q000379:methods / Q000706:statistics & numerical data*; D008875:Middle Aged; D012189:Retrospective Studies